Prof. Bates may be able to give us more recent references on this, but the best literature I know on this is Pinhiero and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer, sec. 2.4). This includes description of a "simulate.lme" function, which you can use to generate random numbers according to a given assumed model and then compare some results with a reference distribution. Something like this could be used to answer your question of what is the correct number of degrees of freedom to use for any particular model.

hope this helps. spencer graves

Douglas Bates wrote:

Contributions of code to provide alternative calculations of
denominator degrees of freedom are welcome :-)

I think it would be good to bear in mind that the use of the t and F
distributions for models with mixed effects is already an
approximation.  If your design is such that you end up with a very few
denominator degrees of freedom then the whole question of whether you
should be using F or t distributions in the first place becomes
problematic.   If the number of denominator degrees of freedom is
moderate than the distinction between alternative methods becomes
unimportant.




______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help

Reply via email to